| A survey on variational autoencoders from a green AI perspective A Asperti, D Evangelista, E Loli Piccolomini SN Computer Science 2 (4), 301, 2021 | 32 | 2021 |
| A green prospective for learned post-processing in sparse-view tomographic reconstruction E Morotti, D Evangelista, E Loli Piccolomini Journal of Imaging 7 (8), 139, 2021 | 15 | 2021 |
| RISING: A new framework for model-based few-view CT image reconstruction with deep learning D Evangelista, E Morotti, EL Piccolomini Computerized Medical Imaging and Graphics 103, 102156, 2023 | 9* | 2023 |
| Dissecting FLOPs along input dimensions for GreenAI cost estimations A Asperti, D Evangelista, M Marzolla International Conference on Machine Learning, Optimization, and Data Science …, 2021 | 9 | 2021 |
| Image embedding for denoising generative models A Asperti, D Evangelista, S Marro, F Merizzi Artificial Intelligence Review 56 (12), 14511-14533, 2023 | 4 | 2023 |
| Graph Laplacian and Neural Networks for Inverse Problems in Imaging: GraphLaNet D Bianchi, M Donatelli, D Evangelista, W Li, EL Piccolomini International Conference on Scale Space and Variational Methods in Computer …, 2023 | 3 | 2023 |
| To be or not to be stable, that is the question: understanding neural networks for inverse problems D Evangelista, J Nagy, E Morotti, EL Piccolomini arXiv preprint arXiv:2211.13692, 2022 | 3 | 2022 |
| Ambiguity in solving imaging inverse problems with deep-learning-based operators D Evangelista, E Morotti, EL Piccolomini, J Nagy Journal of Imaging 9 (7), 133, 2023 | 2 | 2023 |
| A data-dependent regularization method based on the graph Laplacian D Bianchi, D Evangelista, S Aleotti, M Donatelli, EL Piccolomini, W Li arXiv preprint arXiv:2312.16936, 2023 | 1 | 2023 |
| Increasing noise robustness of deep learning-based image processing with model-based approaches E Morotti, D Evangelista, EL Piccolomini Numerical Computations: Theory and Algorithms NUMTA 2023, 155, 2023 | 1 | 2023 |
| Space-Variant Total Variation boosted by learning techniques in few-view tomographic imaging E Morotti, D Evangelista, A Sebastiani, EL Piccolomini arXiv preprint arXiv:2404.16900, 2024 | | 2024 |
| Comparative analysis of conventional and machine learning techniques for rainfall threshold evaluation under complex geological conditions N Dal Seno, D Evangelista, E Piccolomini, M Berti EGU24, 2024 | | 2024 |
| The Future of Formula 1 Racing: Neural Networks to Predict Tyre Strategy EL Piccolomini, D Evangelista, M Rondelli | | |
| Rete Residuale per la Rimozione di Rumore Poissoniano e Gaussiano da Immagini Mediche EL Piccolomini, L Liso, D Evangelista | | |
Elena loli piccolominiProfessor of Numerical Analysis, University of BolognaVerified email at unibo.it
